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DTSTART:20260329T030000
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DTSTAMP:20260825T182614Z
UID:1790587800@ist.ac.at
DTSTART:20260928T113000
DTEND:20260928T123000
DESCRIPTION:Speaker: Francesco Locatello\nhosted by Christoph Lampert\nAbst
 ract: Causality at Machine Learning Scale and ComplexityDistinguishing coi
 ncidence from cause-and-effect relationships is a central challenge in AI 
 (and science): which patterns just co-occur\, and which signal causality? 
 Statistical causality offers a rigorous framework for this question\, but 
 it assumes clean\, low-dimensional\, structured data\, which clashes with 
 the raw\, high-dimensional observations of machine learning applications\,
  including in science. In this talk\, I will present how we can now learn 
 causal structure directly from unstructured data using deep learning\, bri
 dging between the modeling power of causality and the scalability properti
 es of machine learning. I will also highlight some cross-disciplinary coll
 aborations my group has built\, uniquely enabled by ISTA. 
LOCATION:Raiffeisen Lecture Hall\, ISTA
ORGANIZER:diana.zubcevic@ista.ac.at
SUMMARY:Francesco Locatello: Tenure Talk
URL:https://talks-calendar.ista.ac.at/events/6548
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260825T182614Z
UID:1795429800@ist.ac.at
DTSTART:20261123T113000
DTEND:20261123T123000
DESCRIPTION:Speaker: Kim Modic\nhosted by Mikhail Lemeshko
LOCATION:ISTA | Central Building | Raiffeisen Lecture Hall\, ISTA
ORGANIZER:diana.zubcevic@ista.ac.at
SUMMARY:Kim Modic: Tenure Talk | Kim Modic
URL:https://talks-calendar.ista.ac.at/events/6390
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